05 / THE ENGINEER’S BOOKSHELF
What I’m reading, what I’ve finished, and what’s next. A small collection that keeps shaping the way I think about systems and software.
6 books on this shelf
A practical guide to designing scalable, reliable, maintainable systems.
A deep, practical tour of replication, partitioning, transactions, streams, and the real trade-offs behind modern data systems. It helps you reason about correctness, latency, throughput, and failure modes — the exact things that make pipelines trustworthy in production.
Book details ↗A modern overview of the data engineering lifecycle.
Frames data engineering as a product discipline: quality, governance, observability, cost, and ownership. Strong for turning ad-hoc pipelines into reliable data products that teams can trust.
Book details ↗A handbook of agile software craftsmanship.
Even in data engineering, unreadable code creates outages. This book pushes naming, structure, testing discipline, and refactoring habits that keep pipelines and services maintainable.
Book details ↗Professionalism, habits, and decision-making under engineering pressure.
A guide to professional engineering behavior: saying “no” when needed, communication, estimation, and building trust through consistent execution. Great for growing from "good coder" to dependable engineer.
Book details ↗The definitive guide to dimensional modeling.
Explains facts, dimensions, slowly changing dimensions, and patterns that make analytics models understandable and scalable. Still extremely relevant for BI layers and data marts.
Book details ↗Real-time data and stream processing at scale.
Covers Kafka architecture, delivery guarantees, and operational practices. Useful for building CDC pipelines, streaming ingestion, and event-driven integrations without fragile coupling.
Book details ↗